Triple
T38288787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richboro, Pennsylvania |
E1022295
|
entity |
| Predicate | distanceToPhiladelphiaApprox |
P2384
|
FINISHED |
| Object | about 25 miles north |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: about 25 miles north | Statement: [Richboro, Pennsylvania, distanceToPhiladelphiaApprox, about 25 miles north]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPhiladelphiaApprox Context triple: [Richboro, Pennsylvania, distanceToPhiladelphiaApprox, about 25 miles north]
-
A.
distanceToPhiladelphia
chosen
Indicates the spatial distance between a given entity’s location and the city of Philadelphia.
-
B.
distanceToHarrisburg
Indicates the spatial distance between a given entity and the location of Harrisburg.
-
C.
distanceToPittsburgh
Indicates the spatial distance between a given entity’s location and the city of Pittsburgh.
-
D.
distanceToPittsburg
Indicates the spatial distance between a given entity and the location of Pittsburg.
-
E.
distanceToScranton
Indicates the spatial distance between a given entity and the location Scranton.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76df190f081908d5aa02c8a9286d0 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:30 p.m.